{"id":159,"date":"2025-10-23T13:26:03","date_gmt":"2025-10-23T13:26:03","guid":{"rendered":"https:\/\/www.roadside.vision\/case-study\/"},"modified":"2026-03-27T10:28:37","modified_gmt":"2026-03-27T10:28:37","slug":"150-2","status":"publish","type":"page","link":"https:\/\/www.roadside.vision\/en\/150-2\/","title":{"rendered":"Case Study"},"content":{"rendered":"\n
\n
\n

Chrudim & Trees: <\/strong><\/strong>The Results <\/strong><\/strong> <\/h1>\n\n\n\n

How can a city, region, or road administration obtain an up-to-date overview of the state of vegetation in record time<\/strong>? With roadside.vision<\/strong>, it is very simple. See for yourself and watch a short practical demonstration.<\/p>\n\n\n\n

\n

Long story short: <\/strong><\/p>\n\n\n\n

3 days. 200 km. And 10,000 surveyed trees. <\/p>\n<\/blockquote>\n\n\n\n

While vegetation\u2014especially trees\u2014is typically surveyed and subsequently assessed by field workers, roadside.vision utilizes remote sensing methods<\/strong> (vehicle-mounted camera\/LiDAR) or existing databases of panoramic road imagery<\/strong>, similar to Google Street View. The analysis is then handled quickly and reliably by AI<\/strong> thanks to machine learning. <\/p>\n\n\n\n

With almost 100% certainty, we locate and identify individual trees along roadsides, <\/strong>achieving a 90% success rate in urban areas. <\/p>\n<\/div>\n<\/div>\n\n

\n

roadside.vision in numbers <\/strong><\/h2>\n\n\n\n
\n
\n
\"\"<\/span>
\n

Spoiler alert: Transparent pricing based on road kilometers, not tree count.<\/strong>A unique advantage for public tenders. <\/p>\n<\/div><\/div>\n\n\n\n

\n

During 9 hours of driving<\/strong> with a roof-mounted camera, <\/p>\n\n\n\n

225,000<\/strong> photos were generated, <\/p>\n\n\n\n

and in just 2 additional days<\/strong>, <\/p>\n\n\n\n

a complete overview of nearly 10,000 trees <\/strong>was available, <\/p>\n\n\n\n

along approximately 200 km of Chrudim roads<\/strong>.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n

\n

What information does roadside.vision provide?<\/h2>\n\n\n\n
\n
\n
\"\"<\/figure>\n\n\n\n

Detection of existence <\/strong><\/h3>\n\n\n\n